Book Image

Elasticsearch Essentials

Book Image

Elasticsearch Essentials

Overview of this book

With constantly evolving and growing datasets, organizations have the need to find actionable insights for their business. ElasticSearch, which is the world's most advanced search and analytics engine, brings the ability to make massive amounts of data usable in a matter of milliseconds. It not only gives you the power to build blazing fast search solutions over a massive amount of data, but can also serve as a NoSQL data store. This guide will take you on a tour to become a competent developer quickly with a solid knowledge level and understanding of the ElasticSearch core concepts. Starting from the beginning, this book will cover these core concepts, setting up ElasticSearch and various plugins, working with analyzers, and creating mappings. This book provides complete coverage of working with ElasticSearch using Python and performing CRUD operations and aggregation-based analytics, handling document relationships in the NoSQL world, working with geospatial data, and taking data backups. Finally, we’ll show you how to set up and scale ElasticSearch clusters in production environments as well as providing some best practices.
Table of Contents (18 chapters)
Elasticsearch Essentials
Credits
About the Author
Acknowledgments
About the Reviewer
www.PacktPub.com
Preface
Index

Understanding Query-DSL parameters


  • query: The query object contains all the queries that need to be passed to Elasticsearch. For example, the query to find all the documents that belong to a search category can written as follows:

    GET index_name/doc_type/_search
    {
      "query": {
        "query_string": {
     "default_field": "category",
          "query": "search"
        }
      }
    }
  • from and size: These parameters control the pagination and the result size to be returned after querying. The from parameter is used to specify the starting point from which document the results will be returned. It defaults to 0. The size parameter, which defaults to 10, specifies how many top documents will be returned from the total matched documents in a corpus.

  • _source: This is an optional parameter that takes field names in an array format, which are to be returned in the query results. It by default returns all the fields stored inside the _source field. If you do not want to return any field, you can specify _source: false...